Merge pull request #635 from bobmyhill/python_313

Allow numpy 2, python 3.13

Author: bobmyhill

.github/workflows/main.yml

@@ -38,7 +38,7 @@ jobs:
 
     strategy:
       matrix:
-        python-versions: ['3.9', '3.10', '3.11', '3.12']
+        python-versions: ['3.9', '3.10', '3.11', '3.12', '3.13']
 
     steps:
     - uses: actions/checkout@v4
@@ -65,7 +65,7 @@ jobs:
 
     strategy:
       matrix:
-        python-versions: ['3.9', '3.10', '3.11', '3.12']
+        python-versions: ['3.9', '3.10', '3.11', '3.12', '3.13']
 
     steps:
     - uses: actions/checkout@v4

examples/example_fit_composition.py

@@ -191,8 +191,8 @@
     # Create empty arrays to store the weight proportions of each phase,
     # and the principal uncertainties (we do not use the covariances here,
     # although they are calculated)
-    weight_proportions = np.zeros((len(samples), len(phases))) * np.NaN
-    weight_proportion_uncertainties = np.zeros((len(samples), len(phases))) * np.NaN
+    weight_proportions = np.zeros((len(samples), len(phases))) * np.nan
+    weight_proportion_uncertainties = np.zeros((len(samples), len(phases))) * np.nan
 
     # Loop over the samples, fitting phase proportions
     # to the provided bulk composition

misc/benchmarks/slb_2024_benchmarks.py

@@ -183,16 +183,17 @@ def check_fig_3_fcc_ferric_fper():
     fper = SLB_2024.ferropericlase()
     mag = SLB_2024.smag()
 
+    fper.set_composition([0.0, 0.95, 0.01, 0.0, 0.04])
+
     assemblage = simplify_composite_with_composition(
         Composite([fper]), {"Fe": 1.0, "O": 1.1}
     )
     fper = assemblage.phases[0]
 
     composition = {"Fe": 1.0, "O": 1.0}
     assemblage = Composite([bcc, fper, mag], [0.5, 0.49, 0.01])
-    fper.set_composition([0.05, 0.0, 0.95])
     equality_constraints = [["P", 1.0e5], ["phase_fraction", (mag, 0.0)]]
-    sol = equilibrate(composition, assemblage, equality_constraints, tol=1.0e-5)
+    sol = equilibrate(composition, assemblage, equality_constraints)
     T_a_wu_mag = sol[0].assemblage.temperature
     print(f"BCC-fper-mag triple point at 1 bar: {T_a_wu_mag:.2f} K")
 

pyproject.toml

@@ -15,21 +15,22 @@ classifiers = [
     "Programming Language :: Python :: 3.10",
     "Programming Language :: Python :: 3.11",
     "Programming Language :: Python :: 3.12",
+    "Programming Language :: Python :: 3.13",
 ]
 
 [tool.poetry.dependencies]
 python = "^3.8"
-numpy = "^1.24"
+numpy = ">=1.24,<=2.2"
 scipy = "^1.10"
 sympy = "^1.12"
 cvxpy = "^1.3"
 matplotlib = "^3.7"
-numba = "^0.59"
+numba = ">=0.59,<=0.61"
 pycddlib-standalone = {version = "^3.0", optional = true}
 
 [tool.poetry.dev-dependencies]
 ipython = "^8.5"
-numba = "^0.59"
+numba = ">=0.59,<=0.61"
 
 [tool.poetry.extras]
 dev = ["pycddlib-standalone"]

test.sh

@@ -53,7 +53,9 @@ fulldir=$2
 #echo "*** testing $t ..."
 ($PYTHON <<EOF
 import matplotlib as m
+import numpy as np
 m.use('Template')
+np.set_printoptions(legacy='1.25')
 VERBOSE=1
 RUNNING_TESTS=1
 with open('$t') as f:

tutorial/tutorial_04_fitting.ipynb

@@ -483,9 +483,9 @@
         "# Create empty arrays to store the weight proportions of each phase,\n",
         "# and the principal uncertainties (we do not use the covariances here,\n",
         "# although they are calculated)\n",
-        "weight_proportions = np.zeros((len(samples), len(phases)))*np.NaN\n",
+        "weight_proportions = np.zeros((len(samples), len(phases)))*np.nan\n",
         "weight_proportion_uncertainties = np.zeros((len(samples),\n",
-        "                                            len(phases)))*np.NaN\n",
+        "                                            len(phases)))*np.nan\n",
         "\n",
         "residuals = []\n",
         "# Loop over the samples, fitting phase proportions\n",